19 citations · 42 across the 13 of their papers we have counts for
15 papers
Masked Swingers: Harnessing Data Augmentation to Advance Autoencoders for Self-Supervised Learning
Anthony Fuller, Scott C. Lowe, Daniel G. Kyrollos +3
Self-supervised learning (SSL) removes the need for annotations and makes models that are capable across more domains than supervised learning. The autoencoder SSL framework learns…
Planetary Feature Fields are Scalable Earth Representations
Arjun Rao, Sebastian Loeschcke, Anthony Fuller +3
Satellite observations, precomputed embeddings, and map products describe the same evolving Earth, yet are stored as independent, petabyte-scale data products. Their continued grow…
LookThere! Sparse Vision by Reinforced Selection
Sreehari Rammohan, Yousef Yassin, Anthony Fuller +3
Vision transformers typically treat every image token as equally important, yet for most tasks in computer vision only a fraction are needed. Adaptive computation methods accelerat…
Changing Modalities: Adapting Remote Sensing Models to New Satellites and Sensors
Tim G. Zhou, Anthony Fuller, Geoff Pleiss +1
Machine learning models for remote sensing are trained and deployed on a static set of modalities. However, as we equip newer satellites with novel sensors and retire old ones, pra…
No One Knows the State of the Art in Geospatial Foundation Models
Isaac Corley, Nils Lehmann, Caleb Robinson +6
Geospatial foundation models (GFMs) have been proposed as generalizable backbones for disaster response, land-cover mapping, food-security monitoring, and other high-stakes Earth-o…
LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute
Ali Salamatian, Anthony Fuller, Pritam Sarkar +3
Transformers dominate video recognition. They split videos into tokens, and processing them has expensive superlinear computational cost. Yet videos are filled with redundancy, so…
Self-Distillation of Hidden Layers for Self-Supervised Representation Learning
Scott C. Lowe, Anthony Fuller, Sageev Oore +2
The landscape of self-supervised learning (SSL) is currently dominated by generative approaches (e.g. MAE) that reconstruct raw low-level data, and predictive approaches (e.g. I-JE…
Self-Soupervision: Cooking Model Soups without Labels
Anthony Fuller, James R. Green, Evan Shelhamer
Model soups are strange and strangely effective combinations of parameters. They take a model (the stock), fine-tune it into multiple models (the ingredients), and then mix their p…
LookWhere? Efficient Visual Recognition by Learning Where to Look and What to See from Self-Supervision
Anthony Fuller, Yousef Yassin, Junfeng Wen +4
Vision transformers are ever larger, more accurate, and more expensive to compute. The expense is even more extreme at high resolution as the number of tokens grows quadratically w…
Thicker and Quicker: A Jumbo Token for Fast Plain Vision Transformers
Anthony Fuller, Yousef Yassin, Daniel G. Kyrollos +2
ViTs are general and accurate, and address many tasks, but ViTs are slow, and are not always practical when efficiency is key. Existing methods for faster ViTs design hybrid non-Vi…
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
Gabriel Tseng, Anthony Fuller, Marlena Reil +7
We introduce a highly multimodal transformer to represent many remote sensing modalities - multispectral optical, synthetic aperture radar, elevation, weather, pseudo-labels, and m…
LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate
Anthony Fuller, Daniel G. Kyrollos, Yousef Yassin +1
High-resolution images offer more information about scenes that can improve model accuracy. However, the dominant model architecture in computer vision, the vision transformer (ViT…
CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders
Anthony Fuller, Koreen Millard, James R. Green
A vital and rapidly growing application, remote sensing offers vast yet sparsely labeled, spatially aligned multimodal data; this makes self-supervised learning algorithms invaluab…
Under the Cover Infant Pose Estimation using Multimodal Data
Daniel G. Kyrollos, Anthony Fuller, Kim Greenwood +2
Infant pose monitoring during sleep has multiple applications in both healthcare and home settings. In a healthcare setting, pose detection can be used for region of interest detec…
Transfer Learning with Pretrained Remote Sensing Transformers
Anthony Fuller, Koreen Millard, James R. Green
Although the remote sensing (RS) community has begun to pretrain transformers (intended to be fine-tuned on RS tasks), it is unclear how these models perform under distribution shi…